This proposal is to foster my scientific development in order to become an independent clinical investigator. The support sought is for training as a clinical translational scientist with specific expertise in novel brain imaging techniques to serve as the foundation for a career as a leader in the study of cortical lesions (CL) and cognitive impairment (CI) in multiple sclerosis (MS). Until recently little attention was paid to the cognitive aspects of MS. Yet, CI develops in up to 60% of MS patients and is a main factor influencing job productivity and long term disability. The lack of readily available and affordable diagnostic tools prevents early detection and appropriate management that could potentially prolong a patient's financial and social independence. CI is poorly understood at the neurobiological level. Recent studies indicate that CL play a role in MS related CI;previously accurate MRI detection of CL had been suboptimal. In 2005 I was awarded an NIH minority supplement under the parent grant of Ponnada Narayana, PhD. That funding allowed me to complete preliminary but important studies in detection of cortical gray matter lesions. Our studies significantly improved detection and classification of CL, showed that CI correlates with the presence of CL, and supported that the overall MRI-defined damage caused by MS also plays a role. While progress has been made, currently there is no consensus on the most reliable MRI measure for CI detection. The goal of this project is to find accurate, reproducible, easily accessible diagnostic tools for detection of CI by objectively relating CI to brain pathology using multi-modal MRI and neuropsychological (NP) assessments. This will be done by determining correlations between CL detected by novel MRI techniques and findings on functional MRI (fMRI) and diffusion tensor imaging (DTI). The specific aims are: 1) To assess the impact of CL on regional cortical activity as determined by blood oxygen level dependant (BOLD) activation on fMRI;2) To determine the impact of CL on performance of cognition tasks as revealed by fMRI;3) To evaluate the association between abnormalities in BOLD activation on fMRI and integrity of white matter associated pathways as detected by DTI, and 4) To establish the accuracy of CI detection by fMRI paradigms relative to the standard NP testing. The award's training aspects will focus on increasing my knowledge on fMRI physiological principles, activation, experiment design, image processing, and data analysis and interpretation, and will involve structured training in clinical/translational trial design. The MRI Research Division and the Center for Clinical and Translational Sciences (CCTS) at The University of Texas Health Science Center at Houston (UTHSC-H) will provide me with the ideal setting to accomplish this project. Through interaction with mentors Drs. Ponnada Narayana PhD, Jerry Wolinsky MD and Joel Steinberg MD, and an extensive network of experienced researchers, I will further the development of an independent academic career. Assessment of CI by a multimodal MRI approach will increase our understanding of the underlying pathophysiology of CI and may provide an objective, reproducible measure that strongly correlates with the presence and severity of CI. This will significantly improve detection accuracy and translate into early diagnosis/interventions that could improve prognosis for MS patients and provide a foundation for future clinical trials in MS and potentially other fields in the clinical neurosciences. PUBLIC HEALTH RELEVANCE: Cognitive impairment (CI) is an important cause for disability in multiple sclerosis (MS). Diagnosis is made by neuropsychological testing which is limited in availability, expensive and not often covered by insurance. This prevents many patients from being diagnosed and treated. Cortical lesions (CL) play a role in CI. Our group has developed imaging techniques that can detect these lesions. This is the first study that evaluates the effect of CL on cognitive function using functional MRI. We hope to better understand the relationship between CL and CI, find better, more accessible diagnostic tools for CI and hopefully improve prognosis for MS patients.